Cybersecurity in AI-Driven Casual Network Formation

Dmytro Lande, Anatolii Feher, Leonard Strashnoy
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Abstract

The paper describes a methodology for forming thematic causal networks using artificial intelligence and automating the processes of their visualization. The presented methodology is considered on the example of ChatGPT, as an artificial intelligence for analyzing the space of texts and building concepts of causal relationships, and their further visualization is demonstrated on the example of Gephi and CSV2Graph programs. The effectiveness of the disaggregated method in relation to traditional methods for solving such problems is shown by integrating the means of intelligent text analytics and graphical network analysis on the example of the problem of data leakage in information systems and a selection of news clippings on the selected topic.
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人工智能驱动的休闲网络形成中的网络安全
本文描述了一种利用人工智能形成主题因果网络并使其可视化过程自动化的方法。本文提出的方法以ChatGPT为例,作为分析文本空间和构建因果关系概念的人工智能,并以Gephi和CSV2Graph程序为例进行了进一步的可视化演示。通过集成智能文本分析和图形网络分析的手段,以信息系统中的数据泄漏问题为例,并选择有关选定主题的新闻剪报,显示了与解决此类问题的传统方法相比,分类方法的有效性。
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